Communications systems are in the stage of transmission of image as well as simple characters or voice information. For its storage or transmission, video information inevitably requires compression because of its huge amount of information, unlike the information of voice or characters. Among the international standards for the compression of image are joint picture experts group (JPEG) for still pictures, moving picture experts group-1 (MPEG-1) for moving pictures, and moving picture experts group-2 (MPEG-2) for digital TV or HDTV. Together with those, other standards are under way.
Video information is generally duplicate, and video compression is designed to remove this redundancy. A still image roughly involves spatial and statistical redundancies. A moving picture contains temporal redundancy besides the two. For the spatial redundancy, compression is carried out using DPCM or DCT and quantization because spatially nearby pixels have similar values in digital video information. Secondly, the statistical redundancy has compression by allocating a short sign for statistically frequent values and a long sign for statistically rare. Finally, for temporal redundancy, compression is performed by replacing the value of a current picture with the previous because temporally nearby pictures contain similar values except the case where screen conversion occurs.
Those video compression standards essentially include DCT transform. In the original pixel areas video information is widely spread. When the information at the pixel area is DCT transformed, it is converted into spatial frequency area, causing the energy compaction where video information is crowded into the DC value (the mean of image at the pixel area) and low-band frequencies. According to the human visual system (HVS), in the spatial frequency, people are sensitive to the DC value and low-band frequencies but not to high-band frequencies. Therefore, when light quantization is performed in the DC value and low-band frequencies but heavy quantization in the high-band frequencies, compression can be obtained without difference of video quality sensed by people. Among various conversions, the DCT has been suggested as the best in the energy compaction.
FIG. 1 is a block diagram of an encoder of MPEG-2, one of the video standards including DCT transform. Referring to this drawing, there will be described below the compression procedure for input image in the existing encoder, and its drawbacks.
First of all, the intraframe coding construction in the existing encoder includes a first frame memory 11 for storing video signals by frames, an 8*8 pixel divider (not shown) for dividing the video signal stored in first frame memory 11 into 8*8 blocks, an 8*8 DCT transformer 12 for performing DCT transform to the difference between the video signal divided into 8*8 pixel blocks and an output signal of a motion compensator 20 for the purpose of the conversion of the spatial frequency area from pixel area, an 8*8 quantizer 13 for quantizing the signal converted into the spatial frequency area, a variable length coder (VLC) 14 for VLC-coding the signal quantized, a buffer 15 for storing the coded signal in order to send it to a multiplexer at a fixed bit rate, an 8*8 reverse quantizer 16 for reversely quantizing the signal quantized, an 8*8 reverse DCT transformer 17 for converting the reversely quantized signal of the spatial frequency into pixel area, a second frame memory 18 for recovering and storing a decoded image from the output signal of 8*8 reverse DCT transformer 17, a motion predictor 19 for finding motion information between the current and previous images, and the motion compensator 20 for compensating for the motion information detected by motion predictor 19.
As stated above, the conventional video encoder using DCT transform divides a video signal into 8*8 blocks, and signals passing through the 8*8 reverse DCT transformer are compressed through the 8*8 quantizer. However, the 8*8 blocks each have different energy compactions and quantization values in the 8*8 quantizer. For this reason, the output signals of the quantizer contain different values for the respective blocks, involving block effect.
FIG. 2 shows an example of block effect caused by the conventional encoder. As in this picture, the block effect indicates a phenomenon in which the screen appears like mosaic.
FIG. 3 is a block diagram of a conventional decoder of MPEG-2, one of the video compression standards using DCT transform. With FIG. 3, a procedure of decoding an encoded signal into a video signal will be explained below.
A conventional decoder includes a buffer 31 for storing a compressed signal coming at a fixed bit rate, a variable length decoder (VLD) 32 for variable length decoding the output signal of buffer 31 to thereby output a motion vector signal and a quantized signal of spatial frequency, an 8*8 reverse quantizer 33 for reversely quantizing the quantized signal of spatial frequency, an 8*8 reverse DCT transformer 34 for converting the spatial frequency signal into a signal of pixel area, a motion compensator 35 for compensating for motion using a motion vector signal, and a frame memory 36 for storing the signal of pixel area output from the reverse DCT transformer.
FIG. 4 is a block diagram of a conventional decoder for removing block effect. Referring to this drawing, the procedure of eliminating block effect will be explained below.
The decoder includes a buffer 41 for storing a compressed signal coming at a fixed bit rate, a VLD 42 for variable length decoding the output signal of buffer 41 to thereby output a motion vector signal and a quantized signal of spatial frequency, an 8*8 reverse quantizer 43 for reversely quantizing the quantized signal of spatial frequency, a low spatial frequency predictor 47 for presuming five low spatial frequency components, an 8*8 reverse DCT transformer 44 for converting the spatial frequency signal into a signal of pixel area, a motion compensator 45 for compensating for motion using a motion vector signal, and a frame memory 46 for storing the signal of pixel area output from the reverse DCT transformer 44.
FIG. 5 shows the position of blocks used in predicting low spatial frequency, including a block whose low spatial frequency component is presumed, and its nearby blocks used in this process. In this drawing, the current block whose low spatial component is to be predicted is the fifth block, and its DC component is indicated as DC5. Other values in FIG. 5, such as DC1, represent the DC values of nearby blocks used in the procedure.
Referring to FIG. 5, the prediction of low spatial frequency, which substantially removes the block effect, is obtained with expression 1 in which AC(x,y) indicates the frequency component value corresponding to the position of (x,y) in the 8*8 spatial frequency area.
Expression 1 EQU AC.sub.5 (0,1)=1.13885*(DC.sub.4 -DC.sub.6)/8 EQU AC.sub.5 (1,0)=1.13885*(DC.sub.2 -DC.sub.8)/8 EQU AC.sub.5 (2,0)=0.27881*(DC.sub.2 +DC.sub.8 -2*DC.sub.5)/8 EQU AC.sub.5 (1,1)=0.16213*(DC.sub.1 +DC.sub.9 -DC.sub.3 -DC.sub.7)/8 EQU AC.sub.5 (0,2)=0.27881*(DC.sub.4 +DC.sub.6 -2*DC.sub.5)/8
FIG. 6 shows an example of the output image by the conventional block effect removing decoder, explaining the drawbacks of the conventional spatial frequency component predictor. This decoder assumes the spatial frequency component regardless of the contents of image, deteriorating the quality of picture with a complicated image or at the border of objects in the picture. This problem is deemed serious because it occurs at borders where people are very sensitive.